tcai_metaconsciousness

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations available, the description carries the transparency burden. It does disclose a key behavioral trait: the result is a proxy, not a direct measurement. However, it doesn't state whether the tool is read-only, whether it has side effects, or what output range to expect, leaving notable gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is just two sentences. The first sentence enumerates the components of the composite, and the second sentence provides an important qualification. Every word contributes, with no redundancy or irrelevant detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters, no output schema, and no annotations, the description covers the essential aspects: what it is, what it computes, and its proxied nature. It could be more complete by specifying the output format or range, but for a zero-parameter metric it is largely sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and an empty schema, so there are no parameter semantics to explain. The baseline for 0 params is 4, and the description doesn't introduce any confusion or require compensation for undocumented parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool computes a weighted score over four named components (confidence calibration, learning awareness, self-continuity, error monitoring), giving a solid sense of its function. It also disclaims being a proxy rather than a direct measurement, but it doesn't explicitly differentiate from sibling tools like tcai_second_order or tcai_meta_learning.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives. The description explains what the tool produces but never states suitable contexts, prerequisites, or exclusions, and it doesn't mention any sibling tools or alternative approaches.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.